{"id":"https://openalex.org/W4391093668","doi":"https://doi.org/10.1109/bigdata59044.2023.10386972","title":"Integrating Staleness and Shapley Value Consistency for Efficient K-Asynchronous Federated Learning","display_name":"Integrating Staleness and Shapley Value Consistency for Efficient K-Asynchronous Federated Learning","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4391093668","doi":"https://doi.org/10.1109/bigdata59044.2023.10386972"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata59044.2023.10386972","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101710174","display_name":"Yuhui Jiang","orcid":"https://orcid.org/0000-0001-6794-3968"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhui Jiang","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101773230","display_name":"Xingjian Lu","orcid":"https://orcid.org/0000-0002-6935-5614"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingjian Lu","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102884132","display_name":"Wei Mao","orcid":"https://orcid.org/0000-0003-1740-3925"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Mao","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101707186","display_name":"Ying Lin","orcid":"https://orcid.org/0000-0002-2793-5741"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Lin","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":69},"biblio":{"volume":null,"issue":null,"first_page":"680","last_page":"689"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Techniques for Data Analysis and Machine Learning","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Techniques for Data Analysis and Machine Learning","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Optimization Methods in Machine Learning","score":0.9867,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10237","display_name":"Advanced Cryptographic Schemes and Protocols","score":0.9752,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.7381715},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated Learning","score":0.644537},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5562711}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8594536},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.84124},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.7381715},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6218984},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.57721215},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5562711},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5235474},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.46336266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26682663},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20620012},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata59044.2023.10386972","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai","award_id":null},{"funder":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities","award_id":null}],"datasets":[],"versions":[],"referenced_works_count":33,"referenced_works":["https://openalex.org/W2625392185","https://openalex.org/W2886130191","https://openalex.org/W2921434559","https://openalex.org/W2979417040","https://openalex.org/W2998045710","https://openalex.org/W3006017224","https://openalex.org/W3006921589","https://openalex.org/W3008477738","https://openalex.org/W3033511014","https://openalex.org/W3037871107","https://openalex.org/W3038022836","https://openalex.org/W3043723611","https://openalex.org/W3106416029","https://openalex.org/W3118608800","https://openalex.org/W3129775241","https://openalex.org/W3136022984","https://openalex.org/W3159080474","https://openalex.org/W3176364684","https://openalex.org/W3187356235","https://openalex.org/W3198696615","https://openalex.org/W3198837878","https://openalex.org/W3203503583","https://openalex.org/W3208283650","https://openalex.org/W3208693455","https://openalex.org/W3215249070","https://openalex.org/W4211124002","https://openalex.org/W4229029907","https://openalex.org/W4297687186","https://openalex.org/W4302010612","https://openalex.org/W4312424133","https://openalex.org/W4318619660","https://openalex.org/W4320478019","https://openalex.org/W4387353472"],"related_works":["https://openalex.org/W4321854979","https://openalex.org/W4321353415","https://openalex.org/W3037018281","https://openalex.org/W2972592048","https://openalex.org/W2972511296","https://openalex.org/W2944823289","https://openalex.org/W2745001401","https://openalex.org/W2378211422","https://openalex.org/W2358319515","https://openalex.org/W2003209439"],"abstract_inverted_index":{"In":[0,85],"the":[1,30,67,82,104,132,147,152,198],"big":[2],"data":[3,34,79],"era,":[4],"Federated":[5,39],"Learning":[6],"(FL),":[7],"which":[8,102],"allows":[9,124],"multiple":[10,129],"participants":[11],"to":[12,28,111,115,126,165,182],"collaboratively":[13],"train":[14],"a":[15,25,95,157],"global":[16,153],"model":[17,57,83,117,167,175,210],"without":[18],"sharing":[19],"their":[20],"raw":[21],"data,":[22],"emerges":[23],"as":[24],"promising":[26],"solution":[27],"address":[29],"challenges":[31],"of":[32,106,136,151,208],"isolated":[33],"silos":[35],"and":[36,47,60,70,77,108,119,149,169,174,197,212],"privacy":[37],"protection.":[38],"learning":[40],"has":[41],"two":[42],"main":[43],"communication":[44],"strategies:":[45],"synchronous":[46,107],"asynchronous.":[48],"Synchronous":[49],"FL":[50,65,91,99],"ensures":[51],"stable":[52],"convergence":[53,76,120,213],"but":[54,74],"may":[55],"encounter":[56],"quality":[58],"degradation":[59],"server":[61],"crash":[62],"risks.":[63],"Asynchronous":[64],"avoids":[66],"straggler":[68],"effect":[69],"supports":[71],"more":[72,180],"participants,":[73],"unstable":[75],"non-IID":[78],"could":[80],"affect":[81],"performance.":[84],"this":[86],"paper,":[87],"inspired":[88],"by":[89],"real-world":[90],"scenarios,":[92],"we":[93,155,177],"propose":[94],"highly":[96],"efficient":[97],"K-Asynchronous":[98],"framework,":[100],"KFLBSV,":[101],"addresses":[103],"limitations":[105],"asynchronous":[109],"strategies":[110],"some":[112],"extent,":[113],"leading":[114],"improved":[116],"performance":[118,150,211],"speed.":[121,214],"The":[122],"framework":[123],"clients":[125],"upload":[127],"updates":[128],"times":[130],"within":[131],"same":[133],"round":[134],"instead":[135],"blocking":[137],"after":[138],"each":[139,183],"upload,":[140],"thereby":[141],"enhancing":[142],"training":[143],"efficiency.":[144],"To":[145],"ensure":[146],"stability":[148],"model,":[154],"introduce":[156],"novel":[158],"aggregation":[159],"method.":[160],"By":[161],"approximating":[162],"Shapley":[163],"value":[164],"assess":[166],"consistency":[168],"balancing":[170],"client":[171],"contribution":[172],"frequency":[173],"staleness,":[176],"allocate":[178],"weights":[179],"accurately":[181],"participating":[184],"client.":[185],"We":[186],"extensively":[187],"conducted":[188],"experiments":[189],"on":[190],"benchmark":[191],"datasets":[192],"using":[193],"three":[194],"distinct":[195],"models,":[196],"results":[199],"show":[200],"that":[201],"KFLBSV":[202],"outperforms":[203],"existing":[204],"algorithms":[205],"in":[206],"terms":[207],"both":[209]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4391093668","counts_by_year":[],"updated_date":"2024-11-21T11:45:38.072516","created_date":"2024-01-23"}